Analysis of Distributed Algorithms to Remove Correlations for Reducing Average Download Time in Peer-to-Peer Networks

Abstract

The Peer-to-Peer (P2P) networks are widely used for internet file sharing. In general the file download can take minutes or hours depending on the level of network congestion or the service capacity fluctuations. In this paper, we consider two major factors that have significant impact on average download time, namely, the spatial heterogeneity of service capacities in different source peers and the temporal fluctuations in service capacities of a single source peer. We show that both spatial heterogeneity and temporal correlations in service capacity increase the average download time in P2P networks and then analyze a simple, distributed algorithm to reduce the file download time. Here, we analyzes a new algorithms called that effectively remove the negative factors of the existing systems i.e. Parallel downloading, Chunk based switching, periodic switching, thus reduce the average download time. Our algorithm removes correlations in the capacity fluctuations and the heterogeneity in space, thus greatly reducing the average download time.